1. Field of the Invention
The present invention relates to a method of and an apparatus for processing an image, and more particularly to a method of and an apparatus for processing an image while accurately detecting luminance irregularities developed by deficiencies of color filters of a color liquid-crystal display panel.
2. Description of the Related Art
Liquid-crystal display (LCD) panels manufactured according to the semiconductor fabrication technology, particularly the integrated-circuit fabrication technology, suffer a variety of defects. One of such defects is known as a luminance irregularity or an area defect that occurs in a uniform white image which is displayed on an LCD panel.
Luminance irregularities include a luminance irregularity which is brighter than the surrounding image and a luminance irregularity which is darker than the surrounding image. The former luminance irregularity is called a white defect, and the latter luminance irregularity is called a black defect.
Color LCD panels employ color filters of three primaries R (red), G (green), B (blue). Such color LCD panels tend to be defective if color filter materials are not uniformly fixed to the color LCD panel due to a lack of planarity thereof. When an image of a uniform color of R, G, or B is displayed on a color LCD panel using color filters that suffer such a defect, the displayed image is subjected to luminance irregularities. FIG. 1(a) of the accompanying drawings shows luminance irregularities that occur in an image displayed on a color LCD panel. FIG. 1(b) of the accompanying drawings illustrates a change in the luminance along line A-B in the displayed image shown in FIG. 1(a), and FIG. 1(c) of the accompanying drawings illustrates a change in the luminance along line C-D in the displayed image shown in FIG. 1(a).
According to one defect of color filters, a color filter material for a pixel is not fixed in the position of the pixel, but dispersed radially outwardly onto surrounding pixels around the pixel. When an image which is uniform in its entirety and has the same color as the dispersed color filter material is displayed using the defective color filters, backlight passes through the pixel where the color filter material is not fixed, producing an intensively bright white defect, and does not pass through the surrounding pixels because of an increased thickness of the color filter material dispersed over the surrounding pixels, producing a doughnut-shaped or annular black defect, as shown in FIG. 1(b).
According to another defect of color filters, a color filter material for plural pixels is concentrated on a certain pixel, but is not dispersed radially outwardly onto surrounding pixels around the pixel. When an image which is uniform in its entirety and has the same color as the concentrated color filter material is displayed using the defective color filters, backlight does not pass through the pixel where the color filter material is concentrated and has an increased thickness, producing a dark black defect, and passes through the surrounding pixels because the color filter material is not fixed to the surrounding pixels, producing an intensively bright doughnut-shaped or annular white defect, as shown in FIG. 1(c).
The doughnut-shaped black and white defects, whose radius is as large as four or five pixels, produced by a color filter defect corresponding to one pixel are often called a "color stain" because they look like a local "stain" on the color LCD panel.
When a color LCD panel is fabricated, therefore, it is necessary to carry out an image quality inspection process for evaluating the fabricated color LCD panel for any luminance irregularities caused by color filter defects. According to one conventional image quality inspection process, a test image is displayed on the fabricated color LCD panel and visually observed by the inspector, who decides whether the color LCD panel contains a defect or not based on the quality of the observed test image. However, the visual inspection is problematic in that subjective standards for judging test image quality are indefinite, and the resulting judgment tends to vary from inspector to inspector and be affected by fatigue.
In view of the drawbacks of the manual subjective inspection process, there has been developed an automatic image quality inspecting device for inspecting the quality of a test image displayed on a color LCD panel by processing a digital image which is produced by imaging the displayed test image with a high-resolution CCD image sensor. The automatic image quality inspecting device has been made possible by recent image processing technology achievements that permit luminance variations of low contrast to be detected accurately.
The image processing process which is carried out by the automatic image quality inspecting device will be described below. A test image displayed on a color LCD panel which is being inspected is imaged by a high-resolution CCD image sensor, and the data of a digital image (referred to as original image data) produced by the high-resolution CCD image sensor are processed in various fashions to detect a luminance irregularity. The image processing process makes it possible to detect a luminance irregularity which has a contrast level ranging from about 3 to 7% by using filters for noise removal and contrast enhancement and threshold processing. The image processing process will be described in greater detail below.
The original image data contain shading in luminance due to the angle of field of the liquid crystal. Since a change in luminance due to shading is greater than the contrast of luminance irregularities, the image processing process first removes shading in luminance. For the removal of shading, the original image data are processed into smoothed image data by an average filter or a median filter, and the smoothed image data are subtracted from the original image data, thus removing shading. The smoothed image data are referred to as shading image data, and the image data from which shading has been removed are referred to as differential image data.
The differential image data contain luminance irregularities, spike noise introduced when the displayed test image is imaged, and noise comprising shading components which have remain unremoved. These noises are removed by filtering the differential image data. Thereafter, the luminance irregularities contained in the differential image data are detected.
Color stains, however, cannot easily be detected as they are luminance irregularities of a very low contrast level, which experimentally turned out to range from 2 to 3%, caused by a slight difference between color filter thicknesses. Inasmuch as the contrast of color stains is similar to that of noises, if color stains were to be detected with a lowered threshold, then noises would also be detected. Therefore, it is not possible to selectively detect color stains with simple threshold processing.